# \[sparse modelling\] Does JuMP automatically remove "uninfluent" variables from constraints/objective?
**URL:** https://discourse.julialang.org/t/sparse-modelling-does-jump-automatically-remove-uninfluent-variables-from-constraints-objective/81366
**Category:** Optimization (Mathematical)
**Created:** [May 20, 2022, 1:25pm UTC](https://discourse.julialang.org/t/sparse-modelling-does-jump-automatically-remove-uninfluent-variables-from-constraints-objective/81366 "2022-05-20T13:25:09Z")
**Posts on this page:** 7
**Page:** 1
### Author:  [@sylvaticus](https://discourse.julialang.org/u/sylvaticus)
#### Post date: [May 20, 2022, 1:25pm UTC](https://discourse.julialang.org/t/sparse-modelling-does-jump-automatically-remove-uninfluent-variables-from-constraints-objective/81366/1 "2022-05-20T13:25:09Z")
Hello, I am designing a non-linear model where some quantities depend from many variables, but only a few of them actually have a parameter that allow the dependent variable to play.
The actual implementation is:
`quantity_i = prod(price[p]^e[p] for p in products)`
Where a few `e[p]` are actually different than zero.
Is JuMP smart enough to “remove” there variables from the constraint or should I write each constrain separately as to remove the dependency from the uninfluent variables ?
---
### Author:  [@gdalle](https://discourse.julialang.org/u/gdalle)
#### Post date: [May 20, 2022, 1:48pm UTC](https://discourse.julialang.org/t/sparse-modelling-does-jump-automatically-remove-uninfluent-variables-from-constraints-objective/81366/2 "2022-05-20T13:48:04Z")
Do you use a sparse vector to store `e`?
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### Author:  [@sylvaticus](https://discourse.julialang.org/u/sylvaticus)
#### Post date: [May 20, 2022, 1:55pm UTC](https://discourse.julialang.org/t/sparse-modelling-does-jump-automatically-remove-uninfluent-variables-from-constraints-objective/81366/3 "2022-05-20T13:55:30Z")
no. that’s the way to go ?
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### Author:  [@joaquimg](https://discourse.julialang.org/u/joaquimg)
#### Post date: [May 20, 2022, 2:11pm UTC](https://discourse.julialang.org/t/sparse-modelling-does-jump-automatically-remove-uninfluent-variables-from-constraints-objective/81366/4 "2022-05-20T14:11:40Z")
JuMP will not do presolving.
If some variable does not matter for a constraint such as yours you should write them without the variables that do not matter.
---
### Author:  [@sylvaticus](https://discourse.julialang.org/u/sylvaticus)
#### Post date: [May 20, 2022, 2:39pm UTC](https://discourse.julialang.org/t/sparse-modelling-does-jump-automatically-remove-uninfluent-variables-from-constraints-objective/81366/5 "2022-05-20T14:39:38Z")
if the variables that "don’t matter’ is defined in the data (trough a parameter, `e` in my case) rather than in the code is there a way to still keep the structure of the constraint homogeneous ?
My constraints are currently :
```julia
@NLconstraint(m, demand[p in 1:np, r in 1:nr], d[p,r] == const_d[p,r] * prod(pd[p,r]^ e_d[p,r,in_p,in_r] for in_p in 1:np, in_r in 1:nr ) )
@NLconstraint(m, supply[p in 1:np, r in 1:nr], s[p,r] == const_s[p,r] * prod(ps[p,r]^ e_s[p,r,in_p,in_r] for in_p in 1:np, in_r in 1:nr ) )
```
I could add a “logic” to test for `e_d`/`e_d` being equal to zero, but this would be “passed” to the solver I think.
Otherwise I could write many unidimensional constraints, all with a different structure (with the removal of irrelevant variables logic outside the constraint) but how will I get them? by name ?
---
### Author:  [@gdalle](https://discourse.julialang.org/u/gdalle)
#### Post date: [May 20, 2022, 3:44pm UTC](https://discourse.julialang.org/t/sparse-modelling-does-jump-automatically-remove-uninfluent-variables-from-constraints-objective/81366/6 "2022-05-20T15:44:36Z")
Doesn’t it work when the coefficients are sparse though?
---
### Author:  [@odow](https://discourse.julialang.org/u/odow)
#### Post date: [May 22, 2022, 12:13am UTC](https://discourse.julialang.org/t/sparse-modelling-does-jump-automatically-remove-uninfluent-variables-from-constraints-objective/81366/7 "2022-05-22T00:13:02Z")
Does something like this work? (I haven’t tested, so there might be typos, etc.)
```nohighlight
sets = Dict(
(p, r) => [
(inp, inr) for inp in 1:np for inr in 1:nr if !iszero(e_d[p,r,in_p,in_r])
] for p in 1:np, r in 1:nr
)
@NLconstraint(
m,
demand[p in 1:np, r in 1:nr],
d[p,r] == const_d[p,r] * prod(pd[p,r]^e_d[p,r,in_p,in_r] for (in_p, in_r) in sets[(p, r)])
)
```